Envelope protein-specific B cell receptors direct lentiviral vector tropism in vivo.

While studying transgene expression after systemic administration of lentiviral vectors, we found that splenic B cells are robustly transduced, regardless of the types of pseudotyped envelope proteins. However, the administration of two different pseudotypes resulted in transduction of two distinct B cell populations, suggesting that each pseudotype uses unique and specific receptors for its attachment and entry into splenic B cells. Single-cell RNA sequencing analysis of the transduced cells demonstrated that different pseudotypes transduce distinct B cell subpopulations characterized by specific B cell receptor (BCR) genotypes. Functional analysis of the BCRs of the transduced cells demonstrated that BCRs specific to the pseudotyping envelope proteins mediate viral entry, enabling the vectors to selectively transduce the B cell populations that are capable of producing antibodies specific to their envelope proteins. Lentiviral vector entry via the BCR activated the transduced B cells and induced proliferation and differentiation into mature effectors, such as memory B and plasma cells. BCR-mediated viral entry into clonally specific B cell subpopulations raises new concepts for understanding the biodistribution of transgene expression after systemic administration of lentiviral vectors and offers new opportunities for BCR-targeted gene delivery by pseudotyped lentiviral vectors.

Chikungunya virus glycoproteins transform macrophages into productive viral dissemination vessels.

Despite their role as innate sentinels, macrophages are cellular reservoirs for chikungunya virus (CHIKV), a highly pathogenic arthropod-borne alphavirus that has caused unprecedented epidemics worldwide. Here, we took interdisciplinary approaches to elucidate the CHIKV determinants that subvert macrophages into virion dissemination vessels. Through comparative infection using chimeric alphaviruses and evolutionary selection analyses, we discovered for the first time that CHIKV glycoproteins E2 and E1 coordinate efficient virion production in macrophages with the domains involved under positive selection. We performed proteomics on CHIKV-infected macrophages to identify cellular proteins interacting with the precursor and/or mature forms of viral glycoproteins. We uncovered two E1-binding proteins, signal peptidase complex subunit 3 (SPCS3) and eukaryotic translation initiation factor 3 (eIF3k), with novel inhibitory activities against CHIKV production. These results highlight how CHIKV E2 and E1 have been evolutionarily selected for viral dissemination likely through counteracting host restriction factors, making them attractive targets for therapeutic intervention.

A CRISPR Activation Screen Identifies an Atypical Rho GTPase That Enhances Zika Viral Entry.

Zika virus (ZIKV) is a re-emerging flavivirus that has caused large-scale epidemics. Infection during pregnancy can lead to neurologic developmental abnormalities in children. There is no approved vaccine or therapy for ZIKV. To uncover cellular pathways required for ZIKV that can be therapeutically targeted, we transcriptionally upregulated all known human coding genes with an engineered CRISPR-Cas9 activation complex in human fibroblasts deficient in interferon (IFN) signaling. We identified Ras homolog family member V (RhoV) and WW domain-containing transcription regulator 1 (WWTR1) as proviral factors, and found them to play important roles during early ZIKV infection in A549 cells. We then focused on RhoV, a Rho GTPase with atypical terminal sequences and membrane association, and validated its proviral effects on ZIKV infection and virion production in SNB-19 cells. We found that RhoV promotes infection of some flaviviruses and acts at the step of viral entry. Furthermore, RhoV proviral effects depend on the complete GTPase cycle. By depleting Rho GTPases and related proteins, we identified RhoB and Pak1 as additional proviral factors. Taken together, these results highlight the positive role of RhoV in ZIKV infection and confirm CRISPR activation as a relevant method to identify novel host-pathogen interactions.

FPTMS: Frequency-based approach to identify the peptide from the low-energy collision-induced dissociation tandem mass spectra.

The database search method is a widely accepted method to assign a peptide to the tandem mass spectra. In this study, a new flexible method- FPTMS is introduced to interpret the tandem mass spectra with the known peptide sequences in a protein database. Here the frequency of occurrence of fragment ion peaks extracted from the extensive spectral library is used to predict the theoretical tandem mass spectra of the peptides. The dot product scoring and windowed-xcorr scoring methods were implemented to score the experimental spectrum against the theoretical peptide spectra. Windowed-xcorr is introduced to tackle the mass errors and the cleavage position of the fragmentation process. The new method with windowed-xcorr shows an improved identification rate compared to the existing search engines Crux-Tide and X!Tandem at 1% False Discovery Rate (FDR) for the dataset considered in this study. SIGNIFICANCE: Identifying or sequencing of the peptide from tandem mass spectra is an important application in mass spectrometry-based proteomics. Collision-induced dissociation (CID) fragmentation spectra have been widely used to develop a peptide identification algorithm using database search strategy. CID fragmentation behavior is a complex process and found to have dependency on the sequences of peptide, charge state, and residue content. The inclusion of more features of peptide fragmentation behavior and adaptable scoring algorithm improves the efficiency of the peptide identification algorithm.

A Frequency-Based Approach to Predict the Low-Energy Collision-Induced Dissociation Fragmentation Spectra.

Peptide identification algorithms rely on the comparison between the experimental tandem mass spectrometry spectrum and the theoretical spectrum to identify a peptide from the tandem mass spectra. Hence, it is important to understand the fragmentation process and predict the tandem mass spectra for high-throughput proteomics research. In this study, a novel method was developed to predict the theoretical ion trap collision-induced dissociation (CID) tandem mass spectra of the singly, doubly, and triply charged tryptic peptides. The fragmentation statistics of the ion trap CID spectra were used to predict the theoretical tandem mass spectra of the peptide sequence. The study estimated the relative cleavage frequency for each pair of adjacent amino acids along the peptide length. The study showed that the cleavage frequency can be directly used to predict the tandem mass spectra. The predicted spectra show a high correlation with the experimental spectra used in this study; 99.73% of the high-quality reference spectra have correlation scores greater than 0.8. The new method predicts the theoretical spectrum and correlates significantly better with the experimental spectrum as compared to the existing spectrum prediction tools OpenMS_Simulator, MS2PIP, and MS2PBPI, where only 80, 85.76, and 85.80% of the spectral count, respectively, has a correlation score greater than 0.8.